Edge computing-based computer vision and deep transfer learning for high-throughput assessment of Aspergillus flavus infection in crop seedsOA
Edge computing-based computer vision and deep transfer learning for high-throughput assessment of Aspergillus flavus infection in crop seeds
Libin Wu;Liangliang Zhu;Haiyong Weng;Guoping Chen;Hongfei Liu;Yande Liu;Dapeng Ye
School of Mechanical and Automotive Engineering,Xiamen University of Technology,Xiamen,361000,PR China||Fujian Provincial Key Laboratory of Aptamer Technology,900th Hospital of the Joint Logistics Support Force,Fuzhou,350001,Fujian,PR China||Bioresource Engineering Department,McGill University,Montreal,QC,H9X3V9,CanadaCollege of Resources and Environment,Fujian Agriculture and Forestry University,Fuzhou,350002,PR ChinaCollege of Mechanical and Electrical Engineering,Fujian Agriculture and Forestry University,Fuzhou,350002,PR ChinaEconomic Crops Station,Zhangzhou,363000,PR ChinaAopu Tiancheng Optoelectronics Co.,Ltd.,Xiamen,361000,PR ChinaSchool of Mechanical and Automotive Engineering,Xiamen University of Technology,Xiamen,361000,PR ChinaCollege of Mechanical and Electrical Engineering,Fujian Agriculture and Forestry University,Fuzhou,350002,PR China
Edge computingComputer visionDeep transfer learningAspergillus flavusCrop seeds
Edge computingComputer visionDeep transfer learningAspergillus flavusCrop seeds
《植物表型组学（英文）》 2026 (2)
1-12,12
This work was supported by the National Key R&D Program Project,Research and Development of Intelligent and Efficient Processing Technology and Equipment for Vegetable Production Areas(2023YFD2001301).The authors thank the China Scholarship Council(CSC No.202408350068)for the financial support to the author(Libin Wu)to conduct her doctoral research in the Department of Bioresource Engineering at McGill University.
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